Triple
T33321216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ICIAM 2023 Tokyo |
E853138
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object |
ICIAM 2027 conference series
The ICIAM 2027 conference series is a future installment of the International Congress on Industrial and Applied Mathematics, a major global event showcasing advances in applied mathematics and its applications across science, engineering, and industry.
|
E853133
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: ICIAM 2027 conference series | Statement: [ICIAM 2023 Tokyo, relatedTo, ICIAM 2027 conference series]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ICIAM 2027 conference series Triple: [ICIAM 2023 Tokyo, relatedTo, ICIAM 2027 conference series]
Generated description
The ICIAM 2027 conference series is a future installment of the International Congress on Industrial and Applied Mathematics, a major global event showcasing advances in applied mathematics and its applications across science, engineering, and industry.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6df135fd081908c820341af5d9691 |
completed | May 3, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3543321c908190ab0eeb737cbfd02e |
completed | June 19, 2026, 1:25 p.m. |
| NEDg | Description generation | batch_6a3543e43dc8819091abfb05f7e4d523 |
completed | June 19, 2026, 1:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a354505ffd481908b3bc40d99401aa0 |
completed | June 19, 2026, 1:32 p.m. |
Created at: May 1, 2026, 1:33 a.m.